Access method of actuator and control apparatus therefor

ABSTRACT

A method and apparatus for high speed, high precision control of an actuator. An initializing process sets control signals for moving the actuator a set of predetermined distances using fuzzy logic. Control of actuator movement is then performed using these predetermined set control signals and their corresponding distances. Movement of the actuator to target distance lying between the control signal distances are achieved by an interpolation operation using fuzzy logic.

FIELD OF THE INVENTION AND RELATED ART STATEMENT

1. Field of the Invention

The present invention relates generally to an access method of anactuator of a disk memory apparatus and a control apparatus therefor,and more particularly to an access method of the actuator for moving itfrom a starting position to a predetermined target position with a highspeed.

2. Description of Related Art

Recently, the recording capacity of an information recording-reproducingapparatus such as a magnetic disk apparatus or an optical disk apparatushas been significantly increased. Accordingly, improvement in the accessspeed of a transducer to a target track of the magnetic disk or theoptical disk is required in the process of recording or reproducingdata. A Bang-Bang driving method is known as an access control method ofan actuator for positioning the transducer mounted on the actuator ofthe information recording-reproducing apparatus. This method is an openloop control system, and is a minimum time control method which appliesan acceleration command and a deceleration command alternately to theactuator.

FIG. 9 is an actuator driving circuit of an access control apparatus inthe prior art. Referring to FIG. 9, a Bang-Bang command signal 100 of arectangular waveform is applied to the non-invert input (+) of anoperational amplifier 101. The output of the operational amplifier 101is amplified by a power amplifier 102 and is applied to one terminal ofthe magnetic coil 103 of an actuator. The other terminal of the magneticcoil 103 is grounded through a current detection resistor 106. Themagnetic coil 103 has an inductance 104 and a resistance 105 which areconnected in series. A counter electromotive voltage which is generatedin the magnetic coil 103 is represented by a generator 107.

In the circuit, the other terminal of the magnetic coil 103 is coupledto the invert input (-) of the operational amplifier 101. Thereby thecurrent flowing in the magnetic coil 103 is proportional to the inputvoltage at the non-invert input (+) of the operational amplifier 101,and constant current operation is realized within a linear operationrange of the driving circuit. On the other hand, in the event that asufficiently large input voltage is applied to the non-invert input (+)of the operational amplifier 101 such as the Bang-Bang signal 100 shownin FIG. 9, the operational amplifier 101 is saturated, and the drivingcircuit attains an open loop status. Consequently, transistors 102A and102B become alternately conducting, and power source voltages +Ve and-Ve are alternately applied to the magnetic coil 103. This operation isa constant voltage operation.

In the constant voltage operation, the current flowing in the magneticcoil 103 is influenced by the inductance 104 and the counterelectromotive voltage of the magnetic coil 103. Consequently, when theBang-Bang command signal 100 is applied thereto the current flowing themagnetic coil 103 does not vary rapidly, owing to the influence of theinductance 104, at the rise edges 100A and 100C and the fall edge 100B.On the other hand, the counter electromotive voltage of the generator107 increases in proportion to the moving speed of the actuator. Thecounter electromotive voltage serves to decrease the voltage which isapplied to the magnetic coil 103 in the acceleration step of the firsthalf (positive half cycle) of the Bang-Bang command signal 100, andserves to increase the voltage in the deceleration step of the latterhalf of the Bang-Bang command signal 100.

FIG.10(a) is a diagram representing a current I which flows in themagnetic coil 103, FIG.10(b) is a diagram representing the travel speedV of the actuator, and FIG.10(c) is a diagram representing the traveldistance X of the actuator. Abscissa of each diagram is graduated bytime. Referring to FIGS. 10(a), 10(b) and 10(c), when the operation ofthe actuator is not influenced by the inductance 104 and the counterelectromotive voltage, each diagram is illustrated by a dotted line, andwhen the operation of the actuator is influenced by the inductance 104and the counter electromotive voltage, each diagram is illustrated by asolid line.

First, when the operation of the actuator is not influenced by theinductance 104 and the counter electromotive voltage, the travel speed Vof the actuator is evaluated by an integral of the current I, and thetravel distance X is also evaluated by the double-integral of thecurrent which is applied to the actuator. Consequently, an accelerationtime length, and a deceleration time length in which the actuator isaccelerated or decelerated, are calculated according to the travel speedV and the travel distance X at predetermined acceleration anddeceleration which are given by the amplitude of the Bang=Bang commandsignal 100. On the contrary, when the operation of the actuator isinfluenced by the inductance and the counter electromotive voltage, itis very difficult to infer the acceleration time and the decelerationtime with high precision so that the travel speed V becomes zero at atarget position of the actuator. This difficulty is due to thenon-linear characteristic of the inductance and the counterelectromotive voltage. Consequently, an access control apparatus with ahigh precision and a high speed is not realizable by the Bang-Bangdriving method in the prior art.

OBJECT AND SUMMARY OF THE INVENTION

An object of the present invention is to provide an access method of anactuator of a disk memory apparatus and a control apparatus thereforwhich realizes high speed access of the actuator with high precision.

The access method of the actuator in accordance with the presentinvention comprises the steps of:

accessing the actuator by an access command signal including data of anacceleration, an acceleration time, a deceleration and a decelerationtime of the actuator, to move the actuator by a predetermined movingdistance, and

compensating the access command signal on the basis of fuzzy inferencecalculation of plural rules comprising

at least one input variable of an enumeration function based on thepredetermined moving distance and the shift distance between the movingdistance and the moved distance of the actuator, and

at least one output variable having a compensation value of the data ofthe access command signal.

While the novel features of the invention are set forth particularly inthe appended claims, the invention, both as to organization and content,will be better understood and appreciated, along with other objects andfeatures thereof, from the following detailed description taken inconjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG.1 is a block diagram of a control apparatus for realizing an accessmethod of an actuator of an embodiment in accordance with the presentinvention.

FIG.2 is a flow chart of the embodiment of the access method of theactuator in accordance with the present invention;

FIG.3 is a graph representing a relation between a travel distance andan acceleration time of the actuator in the embodiment;

FIGS. 4(a), 4(b) and 4(c) are diagrams of examples of membershipfunctions in the embodiment;

FIGS. 5(a), 5(b), 5(c), 5(d), 5(e) and 5(f) are diagrams representingthe calculation process based on fuzzy inference calculation;

FIGS. 6(a), 6(b) and 6(c) are graphs representing enlarged parts of thegraph shown in FIG.3;

FIGS. 7(a), 7(b) and 7(c) are diagrams of examples of membershipfunctions in the embodiment;

FIG.8 is a block diagram of a fuzzy inference calculation circuit in theembodiment;

FIG.9 is the block diagram of the actuator driving circuit of the accesscontrol apparatus in the prior art;

FIG.10(a) is the waveform of the input Bang-Bang command signal;

FIG.10(b) is the graph of the relation between the travel speed and thetime;

FIG.10(c) is the graph of the relation between the travel distance andthe time.

It will be recognized that some or all of the Figures are schematicrepresentations for purposes of illustration and do not necessarilydepict the actual relative sizes or locations of the elements shown.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG.1 is a circuit block diagram of an access control apparatus of anactuator of an embodiment in accordance with the present invention.Referring to FIG.1, a recording-reproducing transducer of an informationrecording-reproducing apparatus such as an optical disk is mounted on anactuator 7 which is moved by a magnetic driving means 7A. The actuator 7is moved in compliance with a driving signal U, and the transducer ispositioned on a predetermined track of the optical disk, for example.

The position of the actuator 7 is detected by a position encoder 8 and aposition detection circuit 9, and a position signal X is output.Moreover, a moving speed of the actuator 7 is detected by a speeddetection circuit 10 on the basis of the position signal X, and a speedsignal V is output. A control circuit 1 controls the action of theactuator 7 in compliance with an access command signal P which isinputted from an apparatus such as a computer located externally to theaccess control apparatus. The control circuit 1 comprises a fuzzyinference calculation circuit 2, the function of which will becomeapparent from the detailed description given hereinafter, amicrocomputer 3, a memory 4, an interface 5 and a driving signalgeneration circuit 20.

The driving signal generation circuit 20 is an analog switch, forexample, and a driving signal U including data of acceleration, anacceleration time, deceleration and a deceleration time of the actuator7 is applied to the driving circuit 6. Accordingly, a driving outputcurrent I is supplied to the actuator 7. The driving signal U is arectangular bipolar signal, for example, and is similar to the Bang-Bangcommand signal 100 in the prier art. The actuator 7 is accelerated inthe first half of the driving signal U and is decelerated in the latterhalf thereof. The acceleration and deceleration of the actuator 7depends on the amplitude of the driving signal U.

The interface circuit 5 comprises an A/D converter (not shown), and theposition signal X and speed signal V are converted into digital signalsand are applied to the microcomputer 3.

The access command signal P has data of a starting position, a targetposition and a moving direction of the actuator 7, for example, and isinput by the microcomputer 3. The memory 4 temporarily memorizes variousdata.

FIG.2 is a flow chart of an embodiment of the access method of anactuator in accordance with the present invention. The process shown bythe flow chart is performed in a factory prior to delivery of the accesscontrol apparatus to a customer or prior to use by a customer.

A moving range of the actuator 7 is predetermined in accordance with arecording area of an information recording medium and is designated as a"maximum moving distance Xmax". A distance between a starting positionof the actuator 7 (one end of the above-mentioned moving range, forexample) and a target position appointed by an access command is definedas a "moving distance Xd". The range of the moving distance Xd is givenby

    0≦Xd≦Xmax                                    (1)

Subsequently, the maximum moving distance Xmax is divided into (n+1)segments of distance as shown below:

    Xd0, Xd1, Xd2, . . . Xdi, . . . Xdn,

(n: natural number).

Referring to FIG.3, the abscissa is graduated by the moving distancesdivided into the segments as mentioned above (Step 1 in the flow chartshown in FIG.2).

An acceleration time Ti in which the actuator 7 is accelerated to moveit to a position of a distant segment Xdi is calculated by the knownequation (2),

    Ti=(2·Xdi/α).sup.1/2                        (2)

where, the acceleration of the actuator 7 is represented by "α" (Step3). The acceleration time Ti obtained by the relation (2) is atheoretical value, and the influence of a counter electromotive voltagedue to an inductance of the magnetic driving means 7A is not taken intoaccount. After termination of the acceleration time Ti, the actuator 7is decelerated in the latter half of the driving signal U and stops at aposition. Therefore, in order to shift the actuator to a targetposition, an optimum acceleration time must be selected.

The optimum acceleration time will be obtained by trial operation of theactuator 7 on the basis of the acceleration time Ti calculated by theequation (2). The trial operation of the actuator 7 is started withrespect to a first segment between the starting position "0" and thedistance Xd0 shown in FIG.3.

First, the actuator 7 is returned to the starting position "0" (Step 4).The "starting position" is a position at which the actuator 7 staysafter the preceding access operation or one end of the moving range.Then the actuator 7 is accelerated to move to the position of the movingdistance Xd0 during the acceleration time T0, and after termination ofacceleration time the actuator 7 is decelerated. Consequently, theactuator 7 stops at a position. A "shift distance Xdr0" which is definedas the distance measured between the starting position "0" and theposition at which the actuator 7 stops. Then, a "distance variationΔXd0" which is a difference between the moving distance Xd0 and theshift distance Xdr0 is calculated by the relation (3) (Step 6).

    ΔXd0=Xd0-Xdr0                                        (3).

When the distance variation ΔXd0 is sufficiently small (the value willbe shown hereafter) (Step 7), the acceleration time T0 and the movingdistance Xd0 are memorized in the memory 4 (Step 10).

On the other hand, when the distance variation ΔXd0 is not so small, a"compensation time ΔT0" for correcting the acceleration time T0 isevaluated by a fuzzy inference method which will be described hereafter(Step 8). Subsequently, the compensation time ΔT0 is added to theacceleration time T0 as shown by the relation (4), and new accelerationtime T02 is calculated (Step 9).

    T02=T0+ΔT0                                           (4).

Subsequently, the actuator 7 is returned to the starting position "0",and the actuator 7 is moved again to the position of the moving distanceXd0 during the acceleration time T02 (Steps 4, 5). The above-mentionedSteps 4, 5, 6, 7, 8 and 9 are repeated until the distance variation ΔXd0becomes substantially zero. When the distance variation ΔXd0 issubstantially equal to zero, an acceleration time T0 with respect to themoving distance Xd0 is determined, and the date (Xd0, T0) including themoving distance Xd0 and the acceleration time T0 is memorized in thememory 4 (Step 10).

The above-mentioned process of Steps 1-10 is applied to entire movingdistances Xd0, Xd1, Xd2, . . . Xdi . . . Xdn in turn, and data (Xd1, Ti)(i=0, 1, 2, . . . n) of n+1 of number are obtained. The data (Xdi, Ti)are memorized in the memory 4. The data (Xdi, Ti) are shown in FIG.3.Referring to FIG.3, abscissa is graduated by the moving distance Xdi,and the ordinate graduated by the acceleration time Ti.

In the above-mentioned operation, influence of the counter electromotivevoltage due to the inductance of the magnetic driving means 7A can beintroduced into the data (Xdi, Ti) of the acceleration of the actuator7. Consequently, dispersion in the characteristic of the actuator 7 alsocan be compensated.

The details of the fuzzy inference calculation of Step 8 in the flowchart shown in FIG.2 is described below. The fuzzy inference calculationis performed by the fuzzy inference calculation circuit 2 in FIG.1.Basic inference rules are shown as follows:

Rule 1: If ΔXd=PS, then ΔT=PS.

Rule 2: If ΔXd=PM, then ΔT=PM.

Rule 3: If ΔXd=PB, then ΔT=PB.

Rule 4: If ΔXd=NS, then ΔT=NS.

Rule 5: If ΔXd=NM, then ΔT=NM.

Rule 6: If ΔXd=NB, then ΔT=NB.

Rule 7: If ΔXd=ZR, then ΔT=ZR.

Where,

ΔXd: distance variation,

ΔT: compensation time,

PS: positive small,

PM: positive medium,

PB: positive big,

NS: negative small,

NM: negative medium,

NB: negative big,

ZR: zero.

In the above-mentioned inference rules, representation "if ΔXd=PS" iscalled a "situation part", and representation "then ΔT=PS" is called an"action part". Moreover, representations "PS", "PM", "PB", "NS", "NM","NB" and "ZR" are called "fuzzy variables".

The fuzzy inference calculation is elucidated as to the Rule 1, forexample. When a distance variation ΔXd is a positive small value, (theactuator 7 stops before a target position, and the distance variationbetween the arrived position and the target position is small), acompensation time ΔT is a positive small value as shown in the Rule 1.In a similar manner, the above-mentioned fuzzy inference calculation isapplied to the rules 2-7.

According to the graph shown in FIG.3, the abscissa is graduated by themoving distance. This moving distance is divided into the same intervalsbetween the starting position "0" and the moving distance Xdn. On theother hand, the intervals between neighboring two acceleration times Tiand Ti+1 on the ordinate are gradually decreased toward the accelerationtime Tn from the acceleration time T0. The nonlinearity of the relationbetween the moving distance Xdi and the acceleration time Ti is theresult of an actual experiment. The nonlinearity is taken into accountin the fuzzy inference calculation of the embodiment, and the followingfour new inference rules are added to the above-mentioned seven rules:

Rule 8: If Xd=S and ΔXd=PM, then ΔT=PB.

Rule 9: If Xd=S and ΔXd=NM, then ΔT=NB.

Rule 10: If Xd=B and ΔXd=PM, then ΔT=PS.

Rule 11: If Xd=B and ΔXd=NM, then ΔT=NS.

Where,

Xd: moving distance,

S: small,

M: medium,

B: big.

The fuzzy inference calculation mentioned above is elucidated as to theRule 8, for example. When the moving distance Xd is small (S) and thedistance variation ΔXd is positive medium value (PM), the compensationtime ΔT of the acceleration time T is positive big value (PB). Byaddition of the Rule 8, in the event that the moving distance isrelatively small such as moving distance Xd0 or Xd1, a relatively largecompensation time ΔT is added to the acceleration time T. In a similarmanner, the Rules 9-11 are applied to corresponding cases, respectively.Consequently, the effect of the nonlinearity of the curve shown in FIG.3is introduced into the data (Xdi, Ti).

FIGS. 4(a), 4(b) and 4(c) are diagrams of membership functions withrespect to the above-mentioned fuzzy variables. Referring to FIG.4(a),the abscissa is graduated by a moving distance Xd, and the ordinate isgraduated by a grade. The grade takes a value from zero to one. In theembodiment, the maximum moving distance Xmax is 20 mm, and themembership functions are represented by triangles. Referring toFIG.4(b), abscissa is graduated by a distance variation ΔXd of the rangefrom -400 μm to +400 μm. The ordinate is also graduated by the grade.Referring to FIG.4(c), abscissa is graduated by a compensation time ΔTof the range from -400 μsec to +400 μsec. The ordinate is also graduatedby the grade.

FIGS. 5(a), 5(b), 5(c), 5(d), 5(e) and 5(f) are diagrams of a process ofthe fuzzy inference calculation in the embodiment. Referring to thesefigures, the moving distance Xd is 5 mm and the distance variation ΔXdis 150 μm. The fuzzy inference calculation is called the Mamdani methodor MIN-MAX composition method presently known in the art.

Referring to FIG.5(a), the left diagram represents the situation part inRule 1, and the right diagram represents the action part of the samerule. Since the distance variation ΔXd is 150 μm, the grade is 0.5 withrespect to the fuzzy variable PS. Consequently, in the action part, thediagram is cut at the line of the grade 0.5. Thus the variable PS of thecompensation time ΔT is represented by a trapezoid Z1.

Referring to FIG.5(b), the left diagram represents the situation part inRule 2, and the right diagram represents the action part thereof. Thegrade is 0.5 in the situation part. Consequently, the diagram of theaction part is cut along the line of the grade 0.5, and the variable PMof the compensation time ΔT is represented by a trapezoid Z2.

Referring to FIG.5(c), the left diagram represents the situation part inRule 3, and the right diagram represents the action part thereof. In thesituation part, since the grade is zero with respect to the fuzzyvariable PB, the compensation time is not determined in the action part.Consequently, when the distance variation ΔXd is 150 μm, the Rule 3 cannot be applied to the fuzzy variable PB. In a similar manner, Rules 4-7can not be applied to the variable PB.

Referring to FIG.5(d), Rule 8 is applied to the above-mentioned fuzzyinference calculation. The Rule 8 comprises two situation parts and oneaction part. The left diagram represents a moving distance Xd, thecentral diagram represents a distance variation ΔXd and the rightdiagram represents a compensation time ΔT. In the situation parts, sincethe moving distance is 5 mm and the distance variation is 150 μm, boththe grades are 0.5. Consequently, the fuzzy variable PB in the actionpart is represented by a trapezoid Z3.

Referring to FIG.5(e), Rule 9 is applied to the above-mentioned fuzzyinference calculation. In the Rule 9, the left diagram (situation part)represents the variable S, and the grade with respect to 5 mm of themoving distance is 0.5. The central diagram (situation part) representsthe variable NM, and the grade with respect to 150 μm of the distancevariation is zero. Consequently, the grade in the action part withrespect to the variable NB results in zero. Consequently, the Rule 9 cannot be applied to the case. In a similar manner Rules 10 and 11 can notbe applied to the situation.

Referring to FIG.5(f), the diagram of a hatched part represents themembership functions int eh action parts on which he results of thefuzzy calculation with respect to the entire rules from Rule 1 to Rule11 are represented by means of the MIN-MAX composition method. In orderto defuzzify the results, the center of gravity of the hatched part isdetermined. In the example shown in FIG.5(f), 200 μsec of compensationtime ΔT is obtained from the center of gravity.

The compensation time ΔT (200 μsec in this case, for example) is addedto the acceleration time Ti (T=Ti+ΔT), and new acceleration time T iscalculated.

In the embodiment, the driving signal U is a rectangular bipolar signal,and the amplitude of the driving signal U which is applied to theactuator 7 in the acceleration step is identical with that in thedeceleration step, but these amplitudes can be selected arbitrarily. Insuch case, a compensation amplitude ΔD for an acceleration step or adeceleration step is usable for the variable of the action part of afuzzy inference calculation. An example of such a rule having the actionpart of the compensation amplitude ΔD is shown below,

If Xd=S and ΔXd=PM, then ΔD=PB.

Moreover, in the embodiment, a compensation time which compensates adeceleration time is usable as replacement for the compensation time ΔTof the acceleration time T for the variable in the action part.Furthermore, a pause in the moving operation of the actuator 7 can beinterposed between the acceleration step and deceleration step.

As mentioned above, the optimum acceleration time Ti is obtained withrespect to a moving distance Xdi shown by the graph of FIG.3. However,the moving distance Xdi merely represents discrete positions whichdivides the maximum moving distance Xmax into (n+1) segments of themoving distance Xdi. For instance, in order to move the actuator to aposition between both the positions of the moving distances Xd2 and Xd3,an acceleration time T which is larger than the acceleration time T2 andis smaller than the acceleration time T3 must be selected. In theembodiment, the optimum acceleration time T with respect to any movingdistance Xd can be obtained by applying "interpolation operation" to thediscrete moving distance.

FIGS. 6(a), 6(b) and 6(c) are graphs of enlarged parts of the graphshown in FIG.3. Referring to FIG.6(a), the moving distances Xd(i-1) andXdi are illustrated with acceleration times T(i-1) and Ti. When theposition of a moving distance Xd which is targeted is present betweenboth the positions of the moving distances Xd(i-1) and Xdi, theinterpolation acceleration time Td with respect to the moving distanceXd is represented by equation (5) ##EQU1##

The linear interpolation given by the equation (5) interpolates with astraight line L between the intersections P(i-1) and Pi of thecoordinates of the moving distances Xd(i-1) and Xdi and the coordinatescorresponding acceleration times T(i-1) and Ti. However, the relationbetween the moving distance Xdi and the acceleration time Ti is definedby a curve C shown by a dotted line. Therefore, the optimum result isnot realizable only by linear interpolation.

In the present invention, an interpolation operation is applied tocorrect the result of the linear interpolation, and an optimumacceleration time lying on the curve C of the graph of FIG.3 isobtainable.

FIG.6(a) is a diagram of the central part of the curve C shown in FIG.3on an enlarged scale (central part of the moving range of the actuator7), FIG.6(b) is a diagram adjacent to the starting position of theactuator 7 on an enlarged scale, and FIG.6(c) is a diagram adjacent tothe maximum moving distance of the actuator 7 on an enlarged scale.Referring to these figures, the solid line represents the resultantoblique straight lines of the linear interpolation, and curves of thedotted line represent accurate relation between the moving distance Xdand the acceleration time T. Therefore, a vertical difference betweenthe curve and the oblique straight line represents an interpolation timeΔTdi which is an interpolation error of the acceleration time T. Theinterpolation time ΔTdi varies in compliance with the moving distanceXdi. For example, the maximum interpolation time ΔTd0 in the segmentshown in FIG.6(b) is larger than the maximum interpolation time ΔTd(i-1)in the segment shown in FIG.6(a), and the maximum interpolation timeΔTd(n-1) in the segment shown in FIG.6(c) is smaller than theinterpolation time ΔTd(i-1). The above-mentioned size relation is givenby:

    ΔTd(n-1)<ΔTd(i-1)<ΔTd0                   (6).

Referring to FIG.6(a), in interpolation of the interval XI between boththe positions of the moving distances Xd(i-1) and Xdi, the position atwhich an interpolation time ΔTd is maximum is present adjacent to thecenter of the interval XI. Therefore, the interpolation time ΔTd is notin proportion to the moving distance Xd. Consequently, if theinterpolation operation is performed with reference to one of the movingdistance Xd(i-1) and Xdi, the number of Rules undesirably increases inthe fuzzy inference calculation.

It is preferable to reduce the number of Rule in the fuzzy inferencecalculation. In the embodiment, the number of Rule is reduced by thefollowing method;

First, the interval XI is divided into two parts, and the midpoint CP ofthe interval XI is determined. Then, the interpolation operation isperformed with reference to the moving distance Xd(i-1) when the targetposition lies between the position of the moving distance Xd(i-1) andthe midpoint CP. The target position is then represented by[Xd(i-1)+ΔXd]. Moreover, the interpolation operation is performed withreference to the moving distance Xdi when the target position liesbetween the midpoint CP and the position of the moving distance Xdi. Thetarget position is then represented by [Xdi+ΔXd]. Consequently, thedifference variation ΔXd has a positive value in the first half of theinterval XI, and has a negative value in the latter half thereof. Thus,the absolute value of a distance variation ΔXd (|ΔXd|) is used in thefuzzy inference calculation of the interpolation operation. Theabove-mentioned operation is performed by the control circuit 1.

The interpolation time ΔTdi is evaluated by means of a fuzzy inferencecalculation as follows. In the fuzzy inference calculation, inputvariables are the moving distance Xd and a distance variation ΔXd whichis to be added to the moving distance Xd to interpolate the movingdistance Xd, and an output variable is the interpolation time ΔTd. Aninterpolated acceleration time T is obtained by adding the interpolationtime ΔTd to an acceleration time Td. The implicational rules of thefuzzy inference calculation are shown below.

Rule A: If Xd=S and |ΔXd|=S, then ΔTd=M.

Rule B: If Xd=S and |ΔXd|=M, then ΔTd=B.

Rule C: If Xd=S and |ΔXd|=B, then ΔTd=VB.

Rule D: If Xd=M and |ΔXd|=S, then ΔTd=S.

Rule E: If Xd=M and |ΔXd|=M, then ΔTd=M.

Rule F: If Xd=M and |ΔXd|=B, then ΔTd=B.

Rule G: If Xd=B and |ΔXd|=S, then ΔTd=VS.

Rule H: If Xd=B and |ΔXd|=M, then ΔTd=S.

Rule I: If Xd=B and |ΔXd|=B, then ΔTd=M.

The meaning of the fuzzy variables in the implicational rules arefollows:

S: small,

M: medium,

B: big,

VS: very small,

VB: very big.

In FIG.6(a), since the moving distance Xd and the distance variation ΔXdhave medium values (M), it is preferable for the interpolation time ΔTdof an interpolation acceleration time Td to select a medium value (M).Consequently, the Rule E is applied thereto.

In FIG.6(b), since the moving distance Xd is small (S) and the distancevariation ΔXd is medium (M), it is preferable for the interpolation timeΔTd of the interpolation acceleration time Td to select a big value (B).Consequently, the Rule B is applied thereto.

Moreover, in FIG.6(c), since the moving distance Xd is large (B) and thedistance variation ΔXd is medium (M), it is preferable for theinterpolation time ΔTd of the interpolation acceleration time Td toselect a small value (S). Consequently, the Rule H is applied thereto.By a similar criterion mentioned above, preferable rules should beselected for various cases.

The diagrams shown by FIGS. 7(a), 7(b) and 7(c) are examples ofmembership functions with respect to the fuzzy variables. Ordinates aregraduated by the grade between zero and one. Abscissas in FIGS. 7(a),7(b) and 7(c) are graduated by the moving distance Xd, the absolutevalue of the distance variation ΔXd and the interpolation time ΔTd,respectively.

The fuzzy inference calculation by means of the membership functionsshown in FIGS. 7(a), 7(b) and 7(c) are similar to those describedhereinabove with reference to FIGS. 5(a)-5(f).

The interpolation time ΔTd calculated as mentioned above is added to theinterpolation acceleration time Td (T=Td+ΔTd), and an accurateacceleration time T is evaluated. Then the actuator 7 is controlled bythe acceleration time T, and is accurately shifted to a target position.

In the embodiment, the two points P(i-1) and Pi shown in FIG.6(a), forexample, are basically interpolated by a straight line L. Moreover, asreplacement for the linear interpolation by the straight line L, theknown Lagrange interpolation method is applicable thereto. In the eventthat such interpolation method is applied, other fuzzy inference rulesand fuzzy functions may be selected accordingly.

The fuzzy variable in the embodiment can be defined by an enumerationfunction of the moving distance Xd such as Xd^(1/2). In this case, anexample of the rule is represented as follows:

If Xd^(1/2) =S and ΔXd=PM, then ΔT=PB. According to the example of therule, linear relation between the acceleration time T and the movingdistance Xd^(1/2) is obtainable. The linear relation makes easydefinition of membership functions.

A combination of the moving distance Xd and an enumeration function ofthe moving distance Xd is usable for the fuzzy variable int heembodiment. An example of the rule by means of the combination is asfollows:

If Xd+log(Xd)=S and ΔXd =PM, then ΔT=PB.

In the above-mentioned example, linear relation between the accelerationtime T and the combination Xd+log(Xd) is realizable. Consequently,definition of membership functions ar simplified.

FIG.8 is a block diagram of a fuzzy inference calculation circuit 2 inthe embodiment. Referring to FIG.8, a membership function memory 11stores predetermined membership functions. A MIN calculation circuits12.1, 12.2, . . . 12.n comprise memories for storing rules of the fuzzyinference calculation, and serve to calculate situation parts and actionparts thereof. The number of the MIN calculation circuits 12.i (i=1, 2,. . . n) is equal to those of the rules. The output of the MINcalculation circuits 12.i is applied to a MAX calculation circuit 13. Inthe MAX calculation circuit 13, an intersection of sets of themembership functions in the action parts is calculated on the basis ofthe data from the entire MIN calculation circuits 12.i, and resultantdata is inputted to a center of gravity calculation circuit 14. In thecenter of gravity calculation circuit 14, the center of gravity of theintersection of sets is calculated.

Although the present invention has been described in terms of thepresently preferred embodiments, it is to be understood that suchdisclosure is not to be interpreted as limiting. Various alterations andmodifications will no doubt become apparent to those skilled in the artafter having read the above disclosure. Accordingly, it is intended thatthe appended claims be interpreted as covering all alterations andmodifications as fall within the true spirit and scope of the invention.

What is claimed is
 1. A method for initializing an actuator controllerusing fuzzy logic, the method comprising the steps of:dividing apredetermined moving range of said actuator into a plurality of segmentshaving equal length, a beginning of each segment defining a differentdiscrete segment distance from a starting point; determining compensateddrive signals corresponding to each segment distance for moving saidactuator a segment distance, the determining of a compensated drivesignal for a segment distance comprising the steps of,calculating adrive signal which includes data of at least one of acceleration,acceleration time, deceleration, and deceleration time of said actuatorto move said actuator a segment distance, driving said actuator usingsaid calculated drive signal, measuring as a shift distance, a distancesaid actuator moved in response to said calculated drive signal,producing a compensation value by means of a fuzzy inference calculationbased on said segment distance and said shift distance, and compensatingsaid calculated drive signal using said compensation value to produce acompensated drive signal for moving said actuator said segment distance;and storing each of said compensated drive signals for driving saidactuator during operation.
 2. The method as in claim 1, wherein adistance variation is calculated by subtracting said shift distance froma segment distance, and said compensation value is produced by means ofa fuzzy inference calculation based on said distance variation.
 3. Themethod as in claim 1, wherein the compensation value is at least one ofacceleration, acceleration time, deceleration, and deceleration time. 4.A method for initializing an actuator controller and performing controltherewith using fuzzy logic, the method comprising the steps of:dividinga predetermined moving range of said actuator into a plurality ofsegments having equal length, a beginning of each segment defining adifferent discrete segment distance from a starting point; determiningcompensated drive signals corresponding to each segment distance formoving said actuator a segment distance, the determining of acompensated drive signal for a segment distance comprising the stepsof,calculating a drive signal which includes data of at least one ofacceleration, acceleration time, deceleration, and deceleration time ofsaid actuator to move said actuator a segment distance, driving saidactuator using said calculated drive signal, measuring as a shiftdistance, a distance said actuator moved in response to said calculateddrive signal, producing a compensation value by means of a fuzzyinference calculation based on said segment distance and said shiftdistance, and compensating said calculated drive signal using saidcompensation value to produce a compensated drive signal for moving saidactuator said segment distance; storing each of said compensated drivesignals for driving said actuator during operation; inputting an accesscommand signal which has data of a starting position, a target position,and moving direction; reading from storage a first compensated drivesignal corresponding to a segment distance equal to a moving distance,said moving distance being a distance between said starting position andsaid target position; reading from storage second and third compensateddrive signals having second and third segment distances greater than andless than said moving distance when a segment distance does not equalsaid moving distance; interpolating a compensated drive signal fordriving said actuator to move said moving distance based on said secondand third compensated drive signals, said second and third segmentdistances, and said moving distance; producing a correcting value bymeans of a fuzzy inference calculation based on said moving distance andsaid second and third segment distances; correcting said interpolatedcompensated drive signal using said correcting value to produce acorrected drive signal; and driving said actuator using one of saidfirst compensated drive signal and said corrected drive signal.
 5. Themethod as in claim 4, wherein a distance variation is calculated bysubtracting said shift distance from a segment distance, and saidcompensation value is produced by means of a fuzzy inference calculationbased on said distance variation.
 6. The method as in claim 4, whereinthe compensation value is at least one of acceleration, accelerationtime, deceleration, and deceleration time.
 7. The method as in claim 4,wherein after the interpolating step the method comprises the stepsof:calculating a midpoint distance which is halfway between said secondand third segment distances; subtracting said second segment distancefrom said moving distance when said moving distance is less than orequal to said midpoint distance to produce an interpolation distancevariation; and subtracting said midpoint distance from said thirdsegment distance when said moving distance is greater than said midpointdistance to produce an interpolation distance variation; and whereinsaid correcting value is produced by means of a fuzzy inferencecalculation based on said moving distance and said interpolationdistance variation.
 8. A method for controlling an actuator having apredetermined moving range, the predetermined moving range being dividedinto a plurality of segments having beginnings which define differentdiscrete segment distances from a starting point, and compensated drivesignals, corresponding to said segment distances, for driving saidactuator a distance equal to said segment distances, said compensateddrive signals being stored, the method comprising the steps of:inputtingan access command signal which has data of a starting position, a targetposition, and moving direction; reading from storage a first compensateddrive signal corresponding to a segment distance equal to a movingdistance, said moving distance being a distance between said startingposition and said target position; reading from storage second and thirdcompensated drive signals having second and third segment distancesgreater than and less than said moving distance when a segment distancedoes not equal said moving distance; interpolating a compensated drivesignal for driving said actuator to move said moving distance based onsaid second and third compensated drive signals, said second and thirdsegment distances, and said moving distance; producing a correctingvalue by means of a fuzzy inference calculation based on said movingdistance and said second and third segment distances; correcting saidinterpolated compensated drive signal using said correcting value toproduce a corrected drive signal; and driving said actuator using one ofsaid first compensated drive signal and said corrected drive signal. 9.The method as in claim 8, wherein after the interpolating step themethod comprises the steps of:calculating a midpoint distance which ishalfway between said second and third segment distances; subtractingsaid second segment distance from said moving distance when said movingdistance is less than or equal to said midpoint distance to produce aninterpolation distance variation; and subtracting said midpoint distancefrom said third segment distance when said moving distance is greaterthan said midpoint distance to produce an interpolation distancevariation; and wherein said correcting value is produced by means of afuzzy inference calculation based on said moving distance and saidinterpolation distance variation.
 10. An apparatus for initializing anactuator controller using fuzzy logic, comprising:dividing means fordividing a predetermined moving range of said actuator into a pluralityof segments having equal length, a beginning of each segment defining adifferent discrete segment distance from a starting point; calculatingmeans for calculating a drive signal which includes data of at least oneof acceleration, acceleration time, deceleration, and deceleration timeof said actuator to move said actuator a segment distance; drivingsignal output means for outputting said calculated drive signal to drivesaid actuator; measuring means for measuring as a shift distance, adistance said actuator moved in response to said calculated drivesignal; fuzzy inference calculating means for producing a compensationvalue based on said segment distance and said shift distance;compensating means for compensating said calculated drive signal usingsaid compensation value to produce a compensated drive signal for movingsaid actuator said segment distance; and memory means for storing eachof said compensated drive signals for driving said actuator duringoperation.
 11. The apparatus as in claim 10, further comprising a meansfor computing a distance variation by subtracting said shift distancefrom a segment distance, and wherein said fuzzy inference calculatingmeans produces a compensation value based on said distance variation.12. The apparatus as in claim 10, wherein the compensation value is atleast one of acceleration, acceleration time, deceleration, anddeceleration time.
 13. An apparatus for initializing an actuatorcontroller and performing control therewith using fuzzy logic,comprising:dividing means for dividing a predetermined moving range ofsaid actuator into a plurality of segments having equal length, abeginning of each segment defining a different discrete segment distancefrom a starting point; calculating means for calculating a drive signalwhich includes data of at least one of acceleration, acceleration time,deceleration, and deceleration time of said actuator to move saidactuator a segment distance; measuring means for measuring as a shiftdistance, a distance said actuator moved in response to said calculateddrive signal; first fuzzy inference calculating means for producing acompensation value based on said segment distance and said shiftdistance; compensating means for compensating said calculated drivesignal using said compensation value to produce a compensated drivesignal for moving said actuator said segment distance; memory means forstoring each of said compensated drive signals for driving said actuatorduring operation; input means for inputting an access command signalwhich has data of a starting position, a target position, and movingdirection; first reading means for reading from storage a firstcompensated drive signal corresponding to a segment distance equal to amoving distance, said moving distance being a distance between saidstarting position and said target position; second reading means forreading from storage second and third compensated drive signals havingsecond and third segment distances greater than and less than saidmoving distance when a segment distance does not equal said movingdistance; interpolating means for interpolating a compensated drivesignal for driving said actuator to move said moving distance based onsaid second and third compensated drive signals, said second and thirdsegment distances, and said moving distance; second fuzzy inferencecalculating means for producing a correcting value based on said movingdistance and said second and third segment distances; correcting meansfor correcting said interpolated compensated drive signal using saidcorrecting value to produce a corrected drive signal; and driving meansfor driving said actuator using one of said calculated drive signal,said first compensated drive signal and said corrected drive signal. 14.The apparatus as in claim 13, further comprising:midpoint calculatingmeans for calculating a midpoint distance which is halfway between saidsecond and third segment distances; first difference means forsubtracting said second segment distance from said moving distance whensaid moving distance is less than or equal to said midpoint distance toproduce an interpolation distance variation; and second difference meansfor subtracting said midpoint distance from said third segment distancewhen said moving distance is greater than said midpoint distance toproduce an interpolation distance variation; and wherein said secondfuzzy inference calculating means produces said correcting value basedon said moving distance and said interpolation distance variation. 15.The apparatus as in claim 13, further comprising a means for computing adistance variation by subtracting said shift distance from a segmentdistance, and wherein said first fuzzy inference calculation producessaid compensation value based on said distance variation.
 16. Theapparatus as in claim 13, wherein the compensation value is at least oneof acceleration, acceleration time, deceleration, and deceleration time.17. An apparatus for controlling an actuator having a predeterminedmoving range, the predetermined moving range being divided into aplurality of segments having beginnings which define different discretesegment distances from a starting point, and compensated drive signals,corresponding to said segment distances, for driving said actuator adistance equal to said segment distances, said compensated drive signalsbeing stored, the method comprising the steps of:input means forinputting an access command signal which has data of a startingposition, a target position, and moving direction; first reading meansfor reading from storage a first compensated drive signal correspondingto a segment distance equal to a moving distance, said moving distancebeing a distance between said starting position and said targetposition; second reading means for reading from storage second and thirdcompensated drive signals having second and third segment distancesgreater than and less than said moving distance when a segment distancedoes not equal said moving distance; interpolating means forinterpolating a compensated drive signal for driving said actuator tomove said moving distance based on said second and third compensateddrive signals, said second and third segment distances, and said movingdistance; a fuzzy inference calculating means for producing a correctingvalue based on said moving distance and said second and third segmentdistances; correcting means for correcting said interpolated compensateddrive signal using said correcting value to produce a corrected drivesignal; and driving means for driving said actuator using one of saidfirst compensated drive signal and said corrected drive signal.
 18. Theapparatus as in claim 17, further comprising:midpoint calculating meansfor calculating a midpoint distance which is halfway between said secondand third segment distances; first difference means for subtracting saidsecond segment distance from said moving distance when said movingdistance is less than or equal to said midpoint distance to produce aninterpolation distance variation; and second difference means forsubtracting said midpoint distance from said third segment distance whensaid moving distance is greater than said midpoint distance to producean interpolation distance variation; and wherein said fuzzy inferencecalculating means produces said correcting value based on said movingdistance and said interpolation distance variation.